University of Groningen

Novel functional proteins coded by the human genome discovered in metastases ofmelanoma patientsSanchez, Aniel; Kuras, Magdalena; Murillo, Jimmy Rodriguez; Pla, Indira; Pawlowski,Krzysztof; Szasz, A Marcell; Gil, Jeovanis; Nogueira, Fábio C S; Perez-Riverol, Yasset;Eriksson, JonatanPublished in:Cell biology and toxicology

DOI:10.1007/s10565-019-09494-4

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Novel functional proteins coded by the human genomediscovered in metastases of melanoma patients

Aniel Sanchez & Magdalena Kuras & Jimmy Rodriguez Murillo & Indira Pla &

Krzysztof Pawlowski & A. Marcell Szasz & Jeovanis Gil & Fábio C. S. Nogueira &

Yasset Perez-Riverol & Jonatan Eriksson & Roger Appelqvist & Tasso Miliotis &Yonghyo Kim & Bo Baldetorp & Christian Ingvar & Håkan Olsson & Lotta Lundgren &

Henrik Ekedahl & Peter Horvatovich & Yutaka Sugihara & Charlotte Welinder &

Elisabet Wieslander & Ho Jeong Kwon & Gilberto B. Domont & Johan Malm &

Melinda Rezeli & Lazaro Hiram Betancourt & György Marko-Varga

Received: 21 May 2019 /Accepted: 2 September 2019# The Author(s) 2019

Abstract In the advanced stages, malignant melanoma(MM) has a very poor prognosis. Due to tremendousefforts in cancer research over the last 10 years, and theintroduction of novel therapies such as targeted thera-pies and immunomodulators, the rather dark horizon ofthe median survival has dramatically changed from

under 1 year to several years. With the advent of prote-omics, deep-mining studies can reach low-abundantexpression levels. The complexity of the proteome,however, still surpasses the dynamic range capabilitiesof current analytical techniques. Consequently, manypredicted protein products with potential biological

Cell Biol Toxicolhttps://doi.org/10.1007/s10565-019-09494-4

Aniel Sanchez, Magdalena Kuras, Lazaro Hiram Betancourt, andGyörgy Marko-Varga should be considered joint first and lastauthors, respectively.

A. Sanchez (*) : I. Pla :K. Pawlowski : J. MalmSection for Clinical Chemistry, Department of TranslationalMedicine, Skåne University Hospital Malmö, Lund University,205 02 Malmö, Swedene-mail: aniel.sanchez@med.lu.se

M. Kuras : J. R. Murillo : J. Gil : J. Eriksson :R. Appelqvist :Y. Kim :M. Rezeli :L. H. Betancourt (*) :G. Marko-VargaClinical Protein Science & Imaging, Biomedical Centre,Department of Biomedical Engineering, Lund University, BMCD13, 221 84 Lund, Swedene-mail: lazaro.betancourt@med.lu.se

K. PawlowskiBiology, Warsaw University of Life Sciences, Warsaw, Poland

A. M. SzaszCancer Center, Semmelweis University, Budapest 1083, Hungary

F. C. S. Nogueira :G. B. DomontProteomics Unit, Department of Biochemistry, Federal Universityof Rio de Janeiro, Rio de Janeiro, Brazil

F. C. S. NogueiraLaboratory of Proteomics, LADETEC, Institute of Chemistry,Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

Y. Perez-RiverolEuropean Molecular Biology Laboratory, EuropeanBioinformatics Institute (EMBL-EBI), Wellcome Trust GenomeCampus, CB10 1SD Hinxton, Cambridge, UK

T. MiliotisAstraZeneca R&D, Mölndal, Sweden

B. Baldetorp :H. Olsson : L. Lundgren :H. Ekedahl :Y. Sugihara : C. Welinder : E. WieslanderDivision of Oncology and Pathology, Department of ClinicalSciences Lund, Lund University, 221 85 Lund, Sweden

C. IngvarDepartment of Surgery, Clinical Sciences, Skåne UniversityHospital, Lund University, Lund, Sweden

functions have not yet been verified in experimentalproteomic data. This category of ‘missing proteins’(MP) is comprised of all proteins that have been pre-dicted but are currently unverified. As part of the initia-tive launched in 2016 in the USA, the European CancerMoonshot Center has performed numerous deep prote-omics analyses on samples from MM patients. In thisstudy, nine MPs were clearly identified by mass spec-trometry in MM metastases. Some MPs significantlycorrelated with proteins that possess identical PFAMstructural domains; and other MPs were significantlyassociated with cancer-related proteins. This is the firststudy to our knowledge, where unknown and novelproteins have been annotated in metastatic melanomatumour tissue.

Keywords Melanoma .Missing proteins . Tissue .

Biobank . Proteomics . Mass spectrometry

Introduction

Metastatic melanoma is an aggressive disease; pre-viously known to resist most types of therapies.However, the development of targeted therapies intumours with BRAF mutations has revolutionisedtreatment. Nevertheless, a significant number ofpatients with BRAF V600 metastatic melanomaexperience relapse within a few months after treat-ment with the combination of BRAF and MEKinhibitors (Pascale et al. 2018). With the adventof immunotherapy, a significant improvement insurvival has become evident (Eroglu et al. 2018).Nonetheless, the disease often overcomes therapeu-tic blockage of the immune system.

New and promising classification systems andmethods have emerged that have enabled stratificationof patients into refined prognostic clusters. Such

approaches undoubtedly complement available thera-pies. As such, a more uniform prognosis is providedand, more importantly, an improved response to treat-ment (Pimiento et al. 2013; Tímár et al. 2016; Dimitriouet al. 2018). Based on genetic analyses, cutaneous mel-anomas are divided into four classes: BRAF-mutated,RAS-mutated, NF-1-mutated tumours, and triple wild-type (Cancer Genome Atlas Network et al. 2015). Inde-pendent of these sub-groups, immune therapy withcheck-point inhibitors across tumours has resulted inan improved outcome. Applying transcriptomic profil-ing and using paired-end massively parallel sequencingof cDNA together with analyses of high-resolution chro-mosomal copy number data, 11 novel melanoma genefusion products and 12 novel readthrough transcriptshave been identified. From this RNA-seq analysis, asurprisingly high mutational burden was described inmelanoma that was crucial for tumour progression(Berger et al. 2010).

Heterogeneity, clonal expansion and evolutionaryprocesses are further key phenomena that may be re-sponsible for the resistance mechanism of cancer(Marcell Szasz et al. 2019; Turajlic et al. 2019;Swanton 2018). A deeper understanding of single indi-vidual tumour can reveal important pieces of the entirepuzzle. For example, immunotherapies are now admin-istered in earlier stages and it was shown that neoadju-vant ipilimumab + nivolumab expand more tumour-resident T cell clones than adjuvant application (Blanket al. 2018). The adverse effects have prompted furtherstudies and approaches to apply immunotherapies in asafer manner (Bosman et al. 2010).

In order to address unsolved clinical drawbacks, al-ternative research approaches have emerged. Proteo-mics has been successfully applied to several biologicalscenarios as an integral part of multi-omics studies insystem biology and medicine (Collins and Varmus2015; Chen and Snyder 2013).

By nature, proteins are highly complex. Therefore, asa consequence of the dynamic range and sensitivitylimits of current proteomic techniques, many predictedprotein products have not yet been identified in proteo-mic experiments. These proteins could provide essentialclues to aid interpretation of biological processes andpotentially drive new avenues of research and therapeu-tic strategies to solve remaining clinical problems.

In 2016, the Chromosome-centric Human ProteomeProject (C-HPP) launched an initiative to accelerate theidentification and assignment of these ‘missing

Cell Biol Toxicol

L. LundgrenDepartment of Hematology, Oncology and Radiation Physics,Skåne University Hospital, Lund, Sweden

P. HorvatovichDepartment of Analytical Biochemistry, Faculty of Science andEngineering, University of Groningen, Groningen,The Netherlands

H. J. KwonDepartment of Biotechnology, Yonsei University, Seoul, SouthKorea

proteins’(MPs) (Omenn et al. 2017). The proteins weredivided into five groups according to the level of proteinexistence (PE). PE1 contains proteins identified by massspectrometry, 3D structure, immunohistochemistry, and/or amino acid sequencing. PE2 refers to transcript ex-pression, but not protein expression. Proteins annotatedin PE3 do not have any protein or transcript evidence inhumans; however, there are similar sequences that havebeen reported in other species. PE4 proteins arehypothesised from gene models, and the PE5 groupcontains predicted protein sequences with uncertain ev-idence and is mostly associated with pseudogenes (Paiket al. 2018).

The samples in this study are a part of theBioMel biobank, governed by Lund MelanomaStudy Group (LMSG). It is a collection of bloodand tissue (primary and metastases) samples withdetailed clinical information from patients diag-nosed with malignant melanoma in Southern Swe-den. Since 2013, the sample collection is prospective,including fresh frozen tissue and blood. Our biobankcoupled high-end proteomic platform was used to studythe melanoma tumour tissues (Welinder et al. 2015,2017; Welinder et al., 2014a, b; Gil et al. 2019; Kuraset al. 2018; Murillo et al. 2018). We used histopatholog-ical characterisation and a genomic data–directed prote-omic strategy to successfully identify a protein expres-sion pattern that was associated with improved survivalprognostics in lymph node samples from stage 3 malig-nant melanoma patients (Betancourt et al. 2019). Aprogression from locoregional to distantly spread dis-ease was witnessed throughout the years (Fig. 1). In amore recent work, a deeper investigation has been un-dertaken to identify proteins in metastatic disease,namely, those that may be responsible for further pro-gression (Gil et al. 2019).

As a consequence of the high diversity of individuals,it is crucial to perform large-scale analyses of clinicalsamples. This enables the identification of the highestnumber of proteins possible, including proteins thathave never been previously reported by massspectrometry.

In the current study, a novel data set of 33 proteins ispresented. These proteins were identified across 140lymph node metastatic tumour samples from malignantmelanoma patients. All identified proteins are currentlyannotated in Nextprot (Gaudet et al. 2015) as ‘missingproteins’. According to the HUPO guidelines, 9 of theproteins were confidently identified by mass

spectrometry. Association clusters were constructed topinpoint predicted functional annotations for theseproteins.

Materials and methods

This study was approved by the Regional EthicalCommittee at Lund University, Southern Sweden,approval numbers: DNR 191/2007, 101/2013 and2015/266, 2015/618. All patients involved in thestudy provided written informed consent. The ma-lignant melanoma lymph node metastases werecollected from patients undergoing surgical resec-tion at Lund University Hospital, Sweden. Out ofthe 140 tumours included in this study, only fourreceived any of the novel therapies. Nevertheless,the majority of the patients enrolled in the studydied due to the progression of the disease. Histo-pathological analysis of the tissues was performedby a board-certified pathologist (Gil et al. 2019).Protein extraction and digestion were performedaccording to the protocol described by Kuraset al. (2018), and the resultant peptides were la-belled with TMT 11-plex reagents (Thermo FisherScientific, San Jose, CA, USA) according to theinstructions provided. Labelled peptides were sep-arated into 24 fractions by basic reversed-phaseliquid chromatography on a Phenomenex AerisC8 column (100 mm × 2.1 mm, 3.6-μm particles)using an Agilent 1100 HPLC system.

LC-MS/MS analysis was performed on an UltiMate3000 RSLCnano system coupled to a Q Exactive HF-Xmass spectrometer (Thermo Fisher Scientific, San José,CA, USA). Data were acquired in DDA, with the ADPset to off, selecting the top 20 precursors. Full MS scanswere acquired over m/z 350–1400 range at a resolutionof 120,000 (at m/z 200), target AGC value of 3 × 106,maximum injection time of 50 ms, and normalisedcollision energy of 34%. The tandem mass spectra wereacquired in the Orbitrap mass analyser with a resolutionof 45,000, a target ACG value of 1 × 103 and amaximum injection time of 86 ms. An isolationwindow of 0.7 m/z was used and fixed first masswas set to110 m/z. Data were processed with Pro-teome Discoverer v2.3 (Thermo Fisher Scientific,San José, CA, USA) and searched against theHomo sapiens UniProt revised database (2018-10-01), including isoforms, with Sequest HT. Cysteine

Cell Biol Toxicol

carbamidomethylation was set as fixed modifica-tion and methionine oxidation, protein N-terminalacetylation, TMT6plex (+ 229.163 Da) at N-terminal and lysine residues were set as dynamicmodifications. Peptide mass tolerance for the pre-cursor ions and MS/MS spectra were 10 ppm and0.02 Da, respectively.

Protein evidence (PE) was determined using thecriteria adopted from neXtProt and the Chromosome-centric Human Protein Project (C-HPP) (Omennet al. 2018).

Bioinformatics

Missing protein identification

Peptide-spectrum match (PSM), peptide, and proteinidentifications were filtered to less than 1% FDR. Iden-tification and sorting of unique peptides were carriedusing the neXtProt tool ‘Peptide uniqueness checker’(https://www.nextprot.org/tools/peptide-uniqueness-checker) for all peptide sequences from proteinsclassified by neXtProt as P2-P5. PSMs mapping to

Fig. 1 (A) Life history of a melanoma. The image depicts theevolving progression of a malignant melanoma originating fromthe skin, spreading to the lymphatic system and giving rise totransit (intracutaneous) and distant metastases (lung, liver, andeventually brain). The histological images in chronological order:(a) primary nodular melanoma (1×, HE), (b) lymph node metas-tasis (1×, HE), (c) lymph node metastasis composed of epithelioidtumour cells (20×, HE), (d) lung metastasis in fibrotic backgroundand presence of tumour infiltrating lymphocytes (20×, HE), (e)

liver metastasis—note the brisk mitotic activity andmorphologicalchange in cell shape, spindly melanoma cells (20×, HE), (f) brainmetastasis of spindle and ‘monster’ melanocytes (20×, HE). (B)Metastatic melanoma in the lymphatic system in four patients. (a)Small and circumscribed melanoma in a lymph node (1×, HE). (b)Large pigmented melanoma filling the lymph node (1×, HE). (c)Large melanoma with necrotic areas (1×, HE). (d) Melanomabreaking the capsule of the lymph node and infiltrating theneighbouring tissue (20×, HE)

Cell Biol Toxicol

missing proteins were also manually inspected. Allnovel peptides (peptides without MS evidence) werealigned using BLASTp (version: 2.7.1) to threedifferent databases UniProt (release date: 2018),Ensembl (release date: 2019), and RefSeq (releasedate: 2019) as previously suggested (Nesvizhskii 2014). All possible peptide variants were filtered using thefollowing filters: identity score higher 70, less than 2amino acids substitutions with respect to the originalnovel peptide, and theoretical mass within 10 ppm com-pared with the precursor mass. In addition, novel uniquepeptides were searched in PeptideAtlas (http://www.peptideatlas.org) to explore previously reportedevidence in public proteomics data (Fig. 2a).

Structural and functional identification

Structural domains in the novel proteins were identifiedby the conserved domain search tool (Marchler-Baueret al. 2017). Additionally, structural domains were pre-dicted by the FFAS and HHpred algorithms(Jaroszewski et al. 2011; Zimmermann et al. 2018).

The bioinformatics analysis of relational networksbetween proteins that correlatedwith novel PE5 proteinswas performed by ingenuity pathway analysis (IPA,Qiagen, Inc., Redwood City, CA, USA). The querieddata sets that were generated for the PE5 proteins weresignificant as assessed by adjusted p value < 0.01 andincluded proteins with an expression correlation to agiven PE5 protein across the samples in our study.Additionally, IPA provided overrepresented functionalannotations and pathways within the identifiedsubnetworks.

Protein family annotation (PFAM) of the PE2 pro-teins was detected using the DAVID bioinformaticsdatabase (Huang et al. 2009a, b). Spearman rank corre-lation test was performed to determine the correlationcoefficient between PE2 proteins and protein memberswithin the same family. The analysis was based onprotein intensities that were quantitated consideringunique peptides only. Correlations with p values <0.05 were considered significant.

Results and discussions

Well-characterised samples from 140 patients with stage3 malignant melanoma (at the time of tissue collection)were investigated. A robust workflow (Fig. 2a) was

implemented that combines an automated biobank plat-form, advanced high-throughput proteomics, and bioin-formatics. Briefly, the tissue samples were collectedfrom patients and stored with all clinical data in aquality-controlled biobank (Welinder et al. 2013). Thesamples were processed with modern and reproducibleproteomic techniques. To obtain all possible informationrelated to the identified proteins, the data generated wasprocessed with a range of bioinformatics tools.

All novel peptides were mapped to Ensembl, Refseq,and UniProt with allowance for amino acid substitutionsand gaps. The aim was to determine if variants of thesame peptide were apparent in other proteins and couldthus explain the mass spectra. More than 5000 possiblevariants were returned, but none passed the criteria, i.e.,a tryptic peptide with a theoretical mass ± 10 ppm of theexperimental mass.

All tumours are unique in morphology and underly-ing biological processes; however, some drivers areshared amongst melanomas. The high number of proc-essed heterogeneous tumour tissues enabled the identi-fication of 33 ‘missing proteins’ across the 140 samples(Table 1). All proteins were classified according to thePE category reported by neXtProt. Annotations wereapplied according to the HUPO guidelines, namely,‘two or more distinct, uniquely mapping, non-nestedpeptide sequences per protein of length ≥ 9 amino acids’(Omenn et al. 2017). After applying these guidelines,the number of missing proteins was reduced to nine(Table 1) and they can be divided into two groups(PE2 and PE5):

1. Proteins uniquely identified in this study within thecontext of metastatic cancer progression: Q9BSN7(TMEM204), Q8N8Y5 (ZFP41), C9JJ37(BTBD19), Q32M45 (ANO4) although previouslysupported only by transcript presence (PE2)

2. Proteins where the annotation was confirmed andexplicitly linked the proteins to mechanisms of mel-anoma metastasis: Q58FG1 (HSP90AA4P),Q6ZTU2 (EP400P1), Q8IUI4 (Putative SNX29P2),Q58FF7 (HSP90AB3P) , A0A0J9YWL9(TEX13C) while previously marked as proteins ofuncerta in evidence and suspected to bepseudogenes (PE5)

The remaining 24 proteins were identified in up to140 melanoma metastases (Table 1). As most of the

Cell Biol Toxicol

missing proteins are possibly low-abundance proteins(Wei et al. 2016), these results can be considered asfurther evidence to support the existence of the proteinsin the tumours.

Expression correlation is known to be an indicator offunctional association between genes or proteins (Pita-Juárez et al. 2018). Four individual Spearman correla-tion tests were performed to determine if there are anypossible functional associations between the four PE2proteins and well-known proteins with similarities infunction, structure, or sequence. Using the protein in-tensities obtained from the MS data, for each novel

protein, the correlation was assessed against proteinsthat have the same PFAM structural domains.

Two of the four proteins annotated as PE2 (Q8N8Y5/ZFP41 and C9JJ37/BTBD19) were significantly corre-lated with proteins possessing the C2H2 zinc fingerdomain (PF00096) and BTB/POZ domain (PF00651),respectively. Each protein was individually associatedwith one different protein family as shown in Fig. 2B.The Q32945/ANO4 protein was not significantly corre-lated with any proteins of the same family (anoctamin,calcium-activated chloride channel, PF04547); and theQ9BSN7/TMEM204 protein does not have close

Fig. 2 Experimental workflow and information related to the nine‘missing proteins’ reported. (A) A total of 140 MM tissues wereanalysed by LC-MS/MS. MS/MS spectra were contrasted withavailable databases and with annotation levels of protein identifi-cation (PE1-5). Missing proteins were evaluated in terms of pep-tide length, number of peptides, structural and functional analysis,and transcriptomic evidence comparison. (B) Protein spearmancorrelation based on the expression of two of the PE2 proteins

and proteins belong to the Zing Finger, H2H2 type, and BTP/POZdomain. The number of samples and the r value for the spearmancorrelation are represented by n and r respectively. (C) Evidence-based on The Human Atlas for the four PE2 missing proteins inskin tissues, melanoma cell lines (SK-Mel-30), or melanomatissues, TPM (Transcripts per Kilobase Million). (D) Frequencyof identification across the 140 tumour samples; Y-axis representsthe number of samples where the proteins were identified

Cell Biol Toxicol

Tab

le1

Totallisto

f‘m

issing

proteins’identifiedin

thisstudy.The

firstn

ineproteins

wereidentifiedwith

atleast2

peptides

with

≥9am

inoacids

No.

Protein

accessiona

Gene

symbol

Descriptio

nChrom

osom

alpositio

nPeptidesequence

No.of

total

PSMsb

Coverage

[%]c

No.of

samples

detected

d

neXtProt

PElevel

1C9JJ37

BTBD19

BTB/POZdomain-containing

protein19

1p34.1

VGAAVLERPV

AEVAAPV

VK

115

30PE2

QEVFA

HR

1

LALLAPA

ELSA

LEEQNR

1

2Q32M45

ANO4

Anoctam

in-4

12q23.3

ESS

LIN

SDIIFVK

16

20PE2

LHAPW

EVLGR

2

ETLPDLEENDCYTA

PFSQ

QR

1

ISFPQ

WEK

1

3Q8N

8Y5

ZFP

41Zincfingerprotein41

homologue

8q24.3

AFNCGSN

LLK

520

70PE2

EEADVQK

3

TEPCLSP

EDEEHVFD

AFD

ASF

K2

4Q9B

SN7

TMEM204

Transmem

braneprotein204

16p13.3

GLDNDYVESPC

123

80PE2

SCWLV

DR

1

GGPS

PGAR

2

AGQVDAHDCEALGWGSE

AAGFQESR

6

5A0A

0J9Y

WL9

TEX13C

Putativetestis-expressed

protein13C

Xq25

SRPW

NEVEDR

14

10PE5

EMVPL

GDSH

SLK

1

6Q58FF

7HSP

90AB3P

PutativeheatshockproteinHSP

90-beta-3

4q21-q25

SLTSD

WEDHLAVK

336

40PE5

HLEIN

PDHPIMETLR

2

7Q58FG

1HSP

90AA4P

PutativeheatshockproteinHSP

90-alpha

A4

4q35.2

DLIM

DNCEELIPEYLNFIR

919

58PE5

EDLELPE

DEEEK

2

8Q8IUI4

SNX29P2

PutativeproteinSN

X29P2

16p11.2

EST

QNVTLLK

730

60PE5

EST

QGVSS

VFR

3

9Q6Z

TU2-6

EP4

00P1

Isoform

5of

Putativ

eEP4

00-like

protein

12q24.33

QNDLDIEEEEEEHFE

VIN

DEVK

225

80PE5

TSA

AFPAQQQPL

QVLSD

GST

VQLPR

7

10Q5B

KT4

ALG10

Dol-P-G

lc:Glc(2)M

an(9)G

lcNAc(2)-PP-Dol

alpha-1,2-glucosyltransferase

12p11.21

LNIPLPP

TSR

1523

110

PE2

11Q7Z

769

SLC35E3

Solutecarrierfamily

35mem

berE3

12q15

AMTTPV

IIAIQ

TFC

YQK

610

140

PE2

LSE

QEGSR

18

LDIFAPK

18

12Q8T

BE1

CNIH

3Proteincornichonhomologue

31q42.13

SPID

QCNPV

HAR

711

70PE2

13A1L

157

TSPAN11

Tetraspanin-11

12p11.21

TLAENYGQPGATQITASV

DR

117

10PE2

QVPD

SCCK

1

14O14610

GNGT2

Guanine

nucleotide-bindingprotein

G(I)/G(S)/G(O

)subunitg

amma-T2

17q21

EYVEAQAGNDPF

LK

839

70PE2

15O43374

RASA

4Ras

GTPase-activatingprotein4

7q22-q31.1

EAWMEPL

QPT

VR

238

20PE2

16P1

8825

ADRA2C

Alpha-2Cadrenergicreceptor

4p16.1

AGAEGGAGGADGQGAGPG

AAESG

ALT

ASR

16

10PE2

17Q13304

GPR

17Uraciln

ucleotide/cysteinylleukotriene

receptor

2q21

TNESS

LSA

K1

29

PE2

18Q5V

VM6

CCDC30

Coiled-coildomain-containing

protein30

1p34.2

QHNSL

LQEENIK

43

40PE2

ELELEVLK

1

19Q7Z

602

GPR

141

ProbableGproteincoupledreceptor

141

7p14.1

YGIH

EEYNEEHCFK

17

10PE2

Cell Biol Toxicol

Tab

le1

(contin

ued)

No.

Protein

accessiona

Gene

symbol

Descriptio

nChrom

osom

alpositio

nPeptidesequence

No.of

total

PSMsb

Coverage

[%]c

No.of

samples

detected

d

neXtProt

PElevel

20Q86X67

NUDT13

Nucleosidediphosphate-lin

ked

moietyXmotif13

10q22.3

DASL

LST

AQALLR

36

69PE2

HSLLELER

4

21Q8IY85

EFC

AB13

EF-hand

calcium-binding

domain-containing

protein13

17q21.32

EILEEVTK

53

49PE2

ILQSD

FVSE

DNMVNIK

1

22Q9U

PC5

GPR

34ProbableGproteincoupledreceptor

34Xp11.4

IMYHIN

QNK

39

90PE2

FPNSG

K2

YATTA

R4

IMCQLLFR

2

FQGEPS

R1

23Q9Y

5I0

PCDHA13

Protocadherinalpha-13

5q31

VTVLENAFN

GTLV

IK14

680

PE2

24A0A

0A0M

T36

IGKV6D

-21

Immunoglobulin

kappavariable6D

-21

2p11.2

YASQ

SISG

VPS

R8

1670

PE3

25A0A

075B

6S6

IGKV2D

-30

Immunoglobulin

kappavariable2D

-30

2p11.2

VSNWDSG

VPDR

344

30PE3

26Q9B

ZK3

NACA4P

Putativenascentp

olypeptide-associated

complex

subunitalpha-likeprotein

8q22.3

IEDLSQ

EAQLAAAEK

2713

140

PE5

27Q58FF

3HSP

90B2P

Putativeendoplasmin-likeprotein

15q26.3

EFE

PLPN

WVK

2024

130

PE5

28Q96L14

CEP1

70P1

Cep170-likeprotein

4q26

EIN

DVAGEID

SVTSS

GTA

PSTTLV

DR

958

90PE5

29Q9B

YX7

POTEKP

Putativebeta-actin-likeprotein3

2q21.1

LCYVALDSE

QEMAMAASSS

SVEK

129

70PE5

RGMLT

LK

12

30Q8N

F67

ANKRD20A12P

Putativeankyrinrepeatdomain-containing

protein20A12

pseudogene

1q12

LEEIH

LQEQAQYK

111

10PE5

31A2A

3N6

PIPSL

PutativePIP5

K1A

andPSM

D4-likeprotein

10q23.33

SNPE

NNVGLITLDNDCEVLT

TLT

PDTGR

124

10PE5

32Q8IX06

REXO1L

1PPu

tativeexonucleaseGOR

8q21.2

LQEFL

LTQDQLK

14

10PE5

33P0

CG22

DHRS4

L1

Putativedehydrogenase/reductaseSD

Rfamily

mem

ber4-like1

14q11.2

LGEPE

DSL

GIV

SFLCSEDASY

LTGETVMVGGGTPS

R2

297

PE5

aProteinaccessionnumberin

UniProt

database

bTo

taln

umberof

peptide-spectrum

matches

fortheparticular

peptidesequence

cPercentage

oftheproteinsequence

identifiedwith

unique

andnon-unique

peptides

dNum

berof

melanom

atumoursamples

forwhich

theproteinwas

identified

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human homologues in existing protein databases. FFASanalysis of remote sequence similarities, however,showed that TMEM204 is significantly similar toclaudin-like transporters that have known roles in tightjunction and in cancer.

The zinc finger domain proteins have often beenrelated to cancer progression, including several cancerforms, such as breast cancer, gastric cancer, and mela-noma (Cassandri et al. 2017; Lim 2014a). To date,however, specifically, the ZFP41 gene has never beendifferentially detected in any melanoma study. As thisconstitutes the first evidence at the protein level, futurestudies are necessary to relate the expression of theprotein with the progression of melanoma.

Conversely, the BTB/POZ domain-containing pro-teins are known to be involved in several types of

human cancer (Nakayama et al. 2006). The BTBD19gene has been differentially expressed in melanomastudies (Expression Atlas codes (https://www.ebi.ac.uk/arrayexpress/experiment): E-MTAB-6214, E-MTAB-7143). As this is the first time that C9JJ37/BTBD19 has been observed on protein level, futurestudies should be performed to confirm the specific roleof this protein inmelanoma. Of note, both domains (zincfinger and BTB/POZ) are structural sections of theproteins termed ‘ZBTB’, an emerging family of tran-scription factors with active roles in oncogenesis (Leeand Maeda 2012; Lim 2014b).

In addition, expression data analysis of the PE2 pro-teins (genes: BTBD19, ANO4, ZFP41, and TMEM204)revealed that all have been previously observed in skintissues, melanoma cell lines, or melanoma tissues (Fig.

Fig. 3 Functional relationship network for proteins correlated toTEX13C. Ingenuity pathway analysis (IPA) for the proteins sig-nificantly correlated to TEX13C expression in the melanomasamples. Three top protein-protein functional relationship

subnetworks merged. Red, proteins with expression positivelycorrelated to TEX13C. Blue, proteins negatively correlated toTEX13C. Solid lines, direct functional relationships. Dashed lines,indirect relationships

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2C). This evidence was provided by The Human ProteinAtlas (Uhlén et al. 2016; Thul and Lindskog 2018).Taken together, the results are highly supportive of thepresence of such proteins in stage 3 melanoma.

Seven of the nine proteins were quantitated in morethan 30 samples and all nine in more than 10 samples.The identification frequencies of the nine PE2 and PE5proteins during the whole analysis are shown in Fig. 2D.

Five of the nine novel proteins were annotatedpreviously as the ‘suspect’ PE5 proteins (Table 1).Proteins annotated as PE5 typically have little tono information in the literature. Therefore, sets ofproteins with expression patterns across the melanomasamples that correlated with the PE5 proteins identifiedin this study were queried. IPA provided functionalrelational subnetworks enriched in the correlated pro-teins. For TEX13C, IPA analysis of the correlated pro-teins resulted in a relational network that centred onhubs known for their involvement in cancer, such asthe oestrogen receptor ESR1, SMAD3 (Tang et al.2017), TGFB1, and ERK/MAPK kinases (Fig. 3). Theproteins correlated with TEX13C are involved in cell-to-cell signalling and interaction, cellular growth andproliferation, and RNA post-transcriptional modifica-tion. For the proteins that significantly correlated withTEX13C expression, IPA generated the top threeprotein-protein functional relational subnetworks.TEX13C (LOC100129520) is a member of the TEX13family that is comprised of two other members,TEX13A and TEX13B. The latter two proteins havebeen characterised to some extent. TEX13A is anRNA-binding protein (Nguyen et al. 2011) and themouse homologue is a male germ cell–specific nuclearprotein that may be involved in transcriptional repres-sion (Kwon et al. 2016). This protein possesses anuncharacterised structural domain termed TEX13 anda zinc finger domain zf-RanBP (PFAM:PF00641).

Two putative HSP90 heat shock proteins,HSP90AA4P and HSP90AB3P, are close homologuesof the HSP90 chaperones with well-known roles incancer and well-established as cancer drug targets(Mbofung et al. 2017). In this study, we could establishprotein-protein correlations, where 527 and 242 proteinswere found to be significantly correlated withHSP90AB3P and HSP90AA4P, respectively. IPA anal-ysis of these protein data sets yielded RNA post-transcriptional modification as the top, overrepresentedfunctional annotation. Other overrepresented functionalannotations included molecular transport and RNA

trafficking for HSP90AB3P, and protein synthesis andcell morphology for HSP90AA4P.

The EP400P1 protein is a homologue of the E1A-binding chromatin remodeller EP400, albeit containingonly the EP400_N domain with unknown function(Elsesser et al. 2019) and lacking a catalytic DEADnuclease domain. Such an arrangement may indicate aregulatory function that is related to the longer homo-logue, EP400. A large number of proteins correlatedwith the expression of EP400P1 and the top functionalannotations of the group were a cellular compromise,molecular transport, and cellular assembly andorganisation.

The SNX29P2 protein is a homologue of sortingnexins involved in endosomal retromer complex func-tion (Gallon and Cullen 2015), although the proteinlacks important functional domains (the RUN domainthat is probably involved in Ras-like GTPase signallingpathways and the phosphatidylinositol-3-phosphate-binding PX_RUN domain). As such, SNX29P2 can behypothesised as a modulator of the full-length homo-logue, sorting nexin-29. Avery large set of proteins wasobserved to correlate with the expression of SNX29P2and IPA revealed that cellular development, cellulargrowth and proliferation, and cell death and survivalwere the most common annotations amongst these pro-teins. Overall, the sets of proteins that had expressionlevels in the melanoma samples that correlated with thefive novel PE5 proteins are indicative of cancer-relatedfunctions.

In conclusion, new protein evidence for nine ‘miss-ing proteins’ is reported. These were expressed in lymphnode metastases of malignant melanoma. The proteinswere clearly identified across a large-scale analysis ofclinical samples from melanoma patients. Furthermore,associations with cancer-related functions were obtainedand discussed for all the reported proteins.

Funding information Open access funding provided by LundUniversity. This study was financially supported by the BertaKamprad Foundation, ThermoFisher Scientific, Global, andLiconic Biobanking, and was also supported by grants from theNational Research Foundation of Korea, funded by the Koreang o v e r n m e n t ( 2 0 1 5 K 1 A 1 A 2 0 2 8 3 6 5 a n d2016K2A9A1A03904900) and Brain Korea 21 Plus Project, Re-public of Korea, as well as the NIH/NCI International CancerProteogenome Consortium and the Mats and Stefan PaulssonTrust.

Compliance with ethical standards This study was approvedby the Regional Ethical Committee at Lund University, Southern

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Sweden, approval numbers: DNR 191/2007, 101/2013 and2015/266, 2015/618. All patients involved in the study providedwritten informed consent.

Open Access This article is distributed under the terms of theCreative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestrict-ed use, distribution, and reproduction in any medium, providedyou give appropriate credit to the original author(s) and the source,provide a link to the Creative Commons license, and indicate ifchanges were made.

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